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Cloze-style queries are representative problems in reading comprehension. Over the past few months, we have seen much progress that utilizing neural network approach to solve Cloze-style questions. In this paper, we present a novel model called attention-over-attention reader for the Cloze-style reading comprehension task. Our model aims to place another(More)
Reading comprehension has embraced a booming in recent NLP research. Several institutes have released the Cloze-style reading comprehension data, and these have greatly accelerated the research of machine comprehension. In this work, we firstly present Chinese reading comprehension datasets, which consist of People Daily news dataset and Children’s Fairy(More)
Artificial neural networks are powerful models, which have been widely applied into many aspects of machine translation, such as language modeling and translation modeling. Though notable improvements have been made in these areas, the reordering problem still remains a challenge in statistical machine translations. In this paper, we present a novel neural(More)
Most existing approaches for zero pronoun resolution are supervised approaches, where annotated data are released by shared task organizers. Therefore, the lack of annotated data becomes a major obstacle in zero pronoun resolution task. The existing approaches mainly face the challenge of costing manpower on labeling the extended data for better training(More)
In this paper, we describe HIT-LTRC's participation in the IWSLT 2012 evaluation campaign. In this year, we took part in the Olympics Task which required the participants to translate Chinese to English with limited data. Our system is based on Moses, which is an open source machine translation system. We mainly used the phrase-based models to carry out our(More)
Pivot language is employed as a way to solve the data sparseness problem in machine translation, especially when the data for a particular language pair does not exist. The combination of source-to-pivot and pivot-to-target translation models can induce a new translation model through the pivot language. However, the errors in two models may compound as(More)
Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attentions. However, existing reading comprehension datasets are mostly in English. To add diversity in reading comprehension datasets, in this paper we propose a new Chinese reading comprehension dataset for accelerating related research in the community.(More)
For translation between language pairs which is lack of bilingual data, pivot-based SMT uses a pivot language as a “bridge” to generate source-target translation, inducing from source-pivot and pivot-target translation. However, due to the missing of the context information, the reordering model was hard to obtain with the conventional(More)
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